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The snow-shaped distribution network is developed and upgraded from the traditional single-loop network and double-loop network structure. It is composed of three or four groups of single-loop networks in pairs that form a feeder cluster in the form of a ring network. Based on this topology, the coordinated optimization operation problem is studied. First, the game elements are analyzed, and then a cooperative game-based, coordinated optimization operation model is established by taking the minimum network loss and voltage deviation of the system as the utility function. Then, the alternating direction multiplier method (ADMM) is employed in Cplex solver to solve the established optimization model. Finally, a numerical case is given to verify the effectiveness of the proposed model and method. The results show that, by using the complementary difference relationship of source–charge characteristics between different regions in the snow-shaped distribution networks, the cooperative game model can realize the energy interconnection among different regions to improve the operation level.

The increasing incidence of retrogressive thaw slumps (RTSs) in permafrost regions underscores the need for detailed spatial and temporal analysis using InSAR technology to monitor and predict dynamic changes in the process of RTSs. Nevertheless, current InSAR deformation forecasting methods employing deep learning strategies such as the traditional long short-term memory (LSTM) and recent transformer models encounter difficulties in effectively capturing temporal features. Moreover, they are limited in their ability to directly integrate spatial information. In this paper, an innovative deep learning approach named Spacetimeformer is proposed for predicting medium- and short-term InSAR deformation of RTSs in the Chumar River area. This method employs a transformer architecture with a spatiotemporal attention mechanism, which enhances the long-term prediction capabilities of time series models and dynamic spatial modeling. It is applicable to multivariate InSAR spatiotemporal deformation prediction problems. The findings include a list of 72 RTSs compiled based on derived InSAR deformation maps and Sentinel-2 optical images, of which 64 have an average deformation rate exceeding 10 mm/year, indicating signs of permafrost degradation. The density distribution of the displacement maps predicted by the Spacetimeformer model aligned well with the InSAR deformation maps obtained from the small baseline subset (SBAS) method, with the overall prediction deviation controlled within 20 mm. In addition, the point-scale prediction results were compared with LSTM and transformer models. This study indicates that the Spacetimeformer network achieved good results in predicting the deformation of RTSs, with a root mean square error of 1.249 mm. The Spacetimeformer method for deformation prediction with the spacetime mechanism presented in this study can serve as a general framework for multivariate deformation prediction based on InSAR results. It can also quantitatively assess the spatial deformation characteristics and deformation trends of RTSs.

In order to accurately obtain photometric information of high concentration SO42− and other substances in the process industry, the spectroscopy behavior of SO42−, S2−, Ni2+ and Cu2+ in air and nitrogen atmosphere was compared based on the UV-visible spectrophotometer with a nitrogen replacing the oxygen. Different from Ni2+ and Cu2+, the accuracy of SO42− and S2− in the ultraviolet region was effectively improved by using a nitrogen atmosphere (P detection results were regressed within the limited standard range, RE < 5%). The nitrogen atmosphere suppressed the additional light attenuation caused by its absorption of ultraviolet rays by isolating oxygen and was also reflected in the decrease in the degree of red shift of the characteristic wavelength for SO42− with increasing concentration. Therefore, the detection results of SO42− showed an effective improvement in sensitivity. Nevertheless, according to the complementary experimental results and theoretical calculations, in addition to oxygen absorption, the low detection accuracy of SO42− high concentration is also attributed to the reduction of the energy required for electronic excitation per unit group caused by the interaction between SO42− groups, resulting in a deviation of the C-A curve from linearity at high concentrations. The influence of this intermolecular force on the detection results is far more important than oxygen absorption. The research can provide reliable theoretical guidance and technical support for the pollution-free direct measurement of high-concentration solutions in the process industry and promote the sustainable development of the process industry.

Dalinor Lake, the second-largest endorheic salt lake in Inner Mongolia, has shown a shrinking trend given the lack of a significant decrease in precipitation (PRE). Based on high-spatial-resolution datasets, we employed a linear regression model, Theil–Sen median trend analysis, the Mann–Kendall test, and a land use transfer matrix to identify the spatio-temporal distribution and trends of PRE and actual evapotranspiration (AET) at the watershed scale during 2001–2019; then, the water deficit (WD) caused by land use changes in different surface lithology zones was analyzed. The results showed that the annual PRE and WD of the Dalinor Lake watershed showed insignificant upward trends, while the annual AET showed a significant upward trend. Spatially, about 89% of the watershed showed a significant upward trend for AET, while 12% showed a weak significant upward trend for PRE. The WDs of the aeolian sand zone and the sand, gravel, and silt accumulation zone were most heavily affected by the new increased land use from 2001 to 2019, accounting for 43.14% and 25.56% of the total WD of the watershed, respectively. Specifically, the WD of the aeolian sand zone caused by the new increased grassland and farmland in 2019 accounted for 41.92% and 18.52% of the total WD of the zone, respectively. The WD of the sand, gravel, and silt accumulation zone caused by the new increased grassland and farmland in 2019 accounted for 37.07% and 35.59% of the total WD of the zone, respectively. The WD caused by the new increased land use was increased by 7.78 million m3 in 2019 compared with the corresponding land use type in 2001, which would decrease the water yield. It is necessary to strengthen the protection of regional forest ecosystems in the granite and terrigenous clastic rock zone; standardize pasture management and reduce farmland reclamation in the sand, gravel, and silt accumulation zone, the aeolian sand zone, and the basalt platform zone; and reduce unnecessary impervious land construction in the aeolian sand zone.

In a study funded by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), the University of North Dakota (UND) Energy and Environmental Research Center (EERC) performed a first-of-its-kind round-robin interlaboratory study (RRIS) to determine lab-to-lab and method-to-method variability in analyzing the rare earth element (REE) content of domestic resources. Analyses of REEs on eleven different materials were accomplished by the laboratories using four different procedures: ASTM D6357 (Procedure A), ASTM D4503 (Procedure B), an alternate in-house procedure for digestion and REE analysis (Procedure C), and neutron activation analysis (NAA). The results of the RRIS suggest that NAA is the most accurate and reliable method for many of the REEs in these types of materials; however, the method is limited in that it is able to determining only ten of the sixteen REEs. Five of the seven labs reporting data for Procedure A and three of the five labs reporting for Procedure B showed excellent performance in terms of repeatability, reproducibility, agreement with NAA, and SRM recoveries based on AOAC International guidelines on method performance. This indicates that when strictly followed these methods are suitable for REE determination in most materials, although are subject to the overall capabilities and experience of individual laboratories.

Mg-3Sn-1Mn-xLa alloy bars were prepared using backward extrusion, and the effects of the La content on the microstructures and mechanical properties of the alloy were systematically studied using an optical microscope (OM), X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), and tensile tests. The results of this research show that the Mg2Sn phases were mainly formed at the α-Mg grain boundaries and within the grains in the Mg-3Sn-1Mn alloy. After adding a certain amount of La, the plate-shaped MgSnLa compounds consisting of Mg17La2, Mg2Sn, and La5Sn3 gradually disappeared in the α-Mg matrix and grain boundaries. With an increase in La content, the Mg2Sn phase in the crystal was gradually refined and spheroidized. When the content of La reached 1.5%, the tensile strength of the alloy reached 300 Mpa and the elongation reached 12.6%, i.e., 25% and 85% increases, respectively, compared to the Mg-3Sn-1Mn alloy. The plate-shaped compound of Mg-3Sn-1Mn-1.5La had an average length of 3000 ± 50 nm, while the width was 350 ± 10 nm. Meanwhile, the extruded alloy’s grain size was significantly refined, and there were many small cleavage steps and dimples in the fracture surface of the alloy. When the La content reached 2%, the alloy performance showed a downward trend due to the coarsening of the grains. The formed plate-shaped MgSnLa compounds and Mg2Sn phases were consistent with the α-Mg matrix. They effectively pinned the dislocations and grain boundaries, which is the main reason for strengthening the mechanical properties of extrusion alloys.

Post-collisional potassic-ultrapotassic volcanic rocks are widely developed in the Lhasa block, Qinghai-Tibet region. In this paper, it was observed for the first time that dilute alkali elements–Li, Rb, and Cs–exhibit supernormal enrichment in the research data of numerous potassic-ultrapotassic volcanic rocks in the Lhasa block. At the same time, there are few studies on the genesis of enrichment. Currently, 568 sets of published volcanic rock data and 8 sets of measured data in the Lhasa block are sorted in detail, and the genesis of dilute alkali element enrichment is explained by means of geochemical research methods. It is believed that the high degree of magmatic fractionation of potassic-ultrapotassic volcanic rocks in the Lhasa block is the main reason for the abnormal enrichment of dilute alkali elements such as Li, Rb, and Cs. The abnormal enrichment area is mainly located in the central and western parts of the Lhasa block with an age range of 25–13 Ma. The discrimination range of Zr/Hf and Nb/Ta with a high degree of differentiation of potassic-ultrapotassic volcanic rocks in the Lhasa block is divided by analogy with the research results of highly fractionated granites, which provides a reference for the study of the supernormal enrichment of dilute alkali elements in potassic-ultrapotassic volcanic rocks in this area.

Permafrost degradation can significantly affect vegetation, infrastructure, and sustainable development on the Qinghai-Tibet Plateau (QTP). The permafrost on the QTP faces a risk of widespread degradation due to climate change and ecosystem disturbances; thus, monitoring its changes is critical. In this study, we conducted a permafrost surface deformation prediction over the Tuotuo River tributary watershed in the southwestern part of the QTP using the Long Short-Term Memory model (LSTM). The LSTM model was applied to the deformation information derived from a time series of Multi-Temporal Interferometry Synthetic Aperture Radar (MT-InSAR). First, we designed a quadtree segmentation-based Small BAseline Subset (SBAS) to monitor the seasonal permafrost deformation from March 2017 to April 2022. Then, the types of frozen soil were classified using the spatio-temporal deformation information and the temperature at the top of the permafrost. Finally, the time-series deformation trends of different types of permafrost were predicted using the LSTM model. The results showed that the deformation rates in the Tuotuo River Basin ranged between −80 to 60 mm/yr. Permafrost, seasonally frozen ground, and potentially degraded permafrost covered 7572.23, 900.87, and 921.70 km2, respectively. The LSTM model achieved high precision for frozen soil deformation prediction at the point scale, with a root mean square error of 4.457 mm and mean absolute error of 3.421 mm. The results demonstrated that deformation monitoring and prediction using MT-InSAR technology integrated with the LSTM model can be used to accurately identify types of permafrost over a large region and quantitatively evaluate its degradation trends.

The Tibetan Plateau is known as the core area of the third pole of the Earth and is a key area for global climate change research. This study uses the Zabuye Salt Lake travertine dam as the research object and U–Th dating as the chronological framework and proposes that the carbon and oxygen isotopes of travertine can be used as a precipitation index through the analysis of hydrogen and oxygen isotopes of spring water, and petrology, mineralogy, carbon and oxygen isotopes of travertine. The precipitation records of Zabuye Salt Lake over the last 800 years show a dry condition in 1191–1374 AD (Medieval Warm Period), a humid condition in 1374–1884 AD (Little Ice Age), and a dry condition in 1884–1982 AD (Current Warn Period), indicating a warm–dry/cold–moist climate pattern, which is consistent with precipitation records from many places on the Tibetan Plateau. We preliminarily point out that travertine can record the evolution of paleoprecipitation (paleomonsoon) at least on the decadal–centennial scale. The Indian summer monsoon has been the main factor influencing precipitation change in Zabuye Salt Lake over the past 800 years, and the change in evapotranspiration intensity caused by temperature change driven by solar radiation is also an important factor affecting dry–moist change.

Object detection is a basic and important task in the field of aerial image processing and has gained much attention in computer vision. However, previous aerial image object-detection approaches have insufficient use of scene semantic information between different regions of large-scale aerial images. In addition, complex background and scale changes make it difficult to improve detection accuracy. To address these issues, we propose a relationship representation network for object detection in aerial images (RelationRS): (1) Firstly, multi-scale features are fused and enhanced by a dual relationship module (DRM) with conditional convolution. The dual relationship module learns the potential relationship between features of different scales and learns the relationship between different scenes from different patches in a same iteration. In addition, the dual relationship module dynamically generates parameters to guide the fusion of multi-scale features. (2) Secondly, the bridging visual representations module (BVR) is introduced into the field of aerial images to improve the object detection effect in images with complex backgrounds. Experiments with a publicly available object detection dataset for aerial images demonstrate that the proposed RelationRS achieves a state-of-the-art detection performance.

High-precision, real-time, and long-range target geo-location is crucial to UAV reconnaissance and target strikes. Traditional geo-location methods are highly dependent on the accuracies of GPS/INS and the target elevation, which restricts the target geo-location accuracy for LRORS. Moreover, due to the limitations of laser range and the common, real time methods of improving the accuracy, such as laser range finders, DEM and geographic reference data are inappropriate for long-range UAVs. To address the above problems, a set of work patterns and a novel geo-location method are proposed in this paper. The proposed method is not restricted by conditions such as the accuracy of GPS/INS, target elevation, and range finding instrumentation. Specifically, three steps are given, to perform as follows: First, calculate the rough geo-location of the target using the traditional method. Then, according to the rough geo-location, reimage the target. Due to errors in GPS/INS and target elevation, there will be a re-projection error between the actual points of the target and the calculated projection ones. Third, a weighted filtering algorithm is proposed to obtain the optimized target geo-location by processing the reprojection error. Repeat the above process until the target geo-location estimation converges on the true value. The geo-location accuracy is improved by the work pattern and the optimization algorithm. The proposed method was verified by simulation and a flight experiment. The results showed that the proposed method can improve the geo-location accuracy by 38.8 times and 22.5 times compared with traditional methods and DEM methods, respectively. The results indicate that our method is efficient and robust, and can achieve high-precision target geo-location, with an easy implementation.

l-arginine (l-Arg) has been reported to possess a wide range of functions, including anti-inflammatory, anti-oxidative, and anti-apoptosis. However, the role of l-Arg in LPS-induced muscle injury and its potential protective mechanism has not been well elucidated. This study aimed to investigate the effects of l-Arg on the LPS-induced oxidative stress and apoptosis in differentiated C2C12 myotube cells. Our results demonstrated that myotube cells treated with 0.2 mg/mL LPS significantly decreased cell viability. l-Arg treatment significantly suppressed LPS induced ROS accumulation and cell apoptosis. Furthermore, l-Arg improved antioxidant-related enzymes’ activities; increased antioxidant ability via Akt-Nrf2 signaling pathway; maintained the mitochondrial membrane potential (MMP); and enhanced FOXO3a expression, leading to a decrease in the mitochondrial-associated apoptotic proteins. In addition, l-Arg exposure dramatically increased the mRNA and protein expressions of SIRT1. The cytoprotective effect of l-Arg was restricted by the SIRT1 inhibitor EX527, which led to an increase in ROS level, apoptosis rate, and decreased cell MMP. The results also demonstrated that EX527 treatment significantly eliminated the effect of l-Arg on LPS-induced oxidative damage and mitochondria-mediated cell apoptosis. Our findings revealed that l-Arg could be used as a potential nutraceutical in reducing muscle injury via regulating SIRT1-Akt-Nrf2 and SIRT1-FOXO3a-mitochondria apoptosis signaling pathways.

Rock glaciers represent typical periglacial landscapes and are distributed widely in alpine mountain environments. Rock glacier activity represents a critical indicator of water reserves state, permafrost distribution, and landslide disaster susceptibility. The dynamics of rock glacier activity in alpine periglacial environments are poorly quantified, especially in the central Himalayas. Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) has been shown to be a useful technique for rock glacier deformation detection. In this study, we developed a multi-baseline persistent scatterer (PS) and distributed scatterer (DS) combined MT-InSAR method to monitor the activity of rock glaciers in the central Himalayas. In periglacial landforms, the application of the PS interferometry (PSI) method is restricted by insufficient PS due to large temporal baseline intervals and temporal decorrelation, which hinder comprehensive measurements of rock glaciers. Thus, we first evaluated the rock glacier interferometric coherence of all possible interferometric combinations and determined a multi-baseline network based on rock glacier coherence; then, we constructed a Delaunay triangulation network (DTN) by exploiting both PS and DS points. To improve the robustness of deformation parameters estimation in the DTN, we combined the Nelder–Mead algorithm with the M-estimator method to estimate the deformation rate variation at the arcs of the DTN and introduced a ridge-estimator-based weighted least square (WLR) method for the inversion of the deformation rate from the deformation rate variation. We applied our method to Sentinel-1A ascending and descending geometry data (May 2018 to January 2019) and obtained measurements of rock glacier deformation for 4327 rock glaciers over the central Himalayas, at least more than 15% detecting with single geometry data. The line-of-sight (LOS) deformation of rock glaciers in the central Himalayas ranged from −150 mm to 150 mm. We classified the active deformation area (ADA) of all individual rock glaciers with the threshold determined by the standard deviation of the deformation map. The results show that 49% of the detected rock glaciers (monitoring rate greater than 30%) are highly active, with an ADA ratio greater than 10%. After projecting the LOS deformation to the steep slope direction and classifying the rock glacier activity following the IPA Action Group guideline, 12% of the identified rock glaciers were classified as active and 86% were classified as transitional. This research is the first multi-baseline, PS, and DS network-based MT-InSAR method applied to detecting large-scale rock glaciers activity.

In China, pre-Quaternary solid potash deposit has only been discovered in the Simao Basin, and the Lower Cretaceous Mengyejing (MYJ) Formation (Fm.) is the productive layer of potash deposit. In this study, we investigated the clay conglomerates which are distributed in upper and lower members of the potash-bearing salt rock layer. We analyzed the relative contents of major elements (Al2O3, Fe2O3T, MgO, CaO, Na2O, K2O) and trace elements (B, Ba, Co, Cr, Cu, Ga, Mn, Ni, Rb, Sr, V, Zn, Zr) in the samples. The results show that MgO and CaO in the major elements are rich relative to Post Archean Australian Shale (PAAS), whose average enrichment factor values of the MgO (EFMgO) is 2.61 and CaO (EFCaO) is 4.57, and the others major elements are relatively minor; trace elements (B, Ga, Mn, Zr) are rich relative to PAAS, and the others trace elements are minor relative to PAAS. The study of paleogeographic conditions using various parameters shows that the paleoclimate is generally dry and hot during the period of clay conglomerate deposition, but it was warm and humid in certain periods; the main sedimentary environment is weak oxidation condition with strong oxidation conditions in individual periods; the average value of paleosalinity is ~21‰, and the highest is no more than ~92‰. The significance of the paleogeographic characteristics of MYJ Fm. to potash mineralization are as follows: (1) they indicates that the clay conglomerates of MYJ Fm. are not clastic sediments in brine formed by seawater, because the paleosalinity of clay conglomerates deposition period is obviously lower than that of seawater; (2) MYJ potassic salt ore is not formed by evaporation and concentration of seawater in clay conglomerates in the sedimentary basin, because there is no carbonate rock and sulfate rock of corresponding scale after the deposition of clay conglomerates in the basin; (3) clay conglomerates of MYJ Fm. were deposited in continental shallow water basin; (4) the matter source of potash minerals is deep marine strata; (5) in the MYJ Fm. sedimentation period, deep source salt moved to the surface under the background of extensional structure, and the subsequent sedimentary clastic rock formed a protective layer of potash-bearing rock, thus completing the “deep source and shallow mineralization” metallogenic process.

The dynamic changes of the thawing and freezing processes of the active layer cause seasonal subsidence and uplift over a large area on the Qinghai–Tibet Plateau due to ongoing climate warming. To analyze and investigate the seasonal freeze–thaw process of the active layer, we employ the new small baseline subset (NSBAS) technique based on a piecewise displacement model, including seasonal deformation, as well as linear and residual deformation trends, to retrieve the surface deformation of the Beiluhe basin. We collect 35 Sentinel-1 images with a 12 days revisit time and 9 TerraSAR-X images with less-than two month revisit time from 2018 to 2019 to analyze the type of the amplitude of seasonal oscillation of different ground targets on the Beiluhe basin in detail. The Sentinel-1 results show that the amplitude of seasonal deformation is between −62.50 mm and 11.50 mm, and the linear deformation rate ranges from −24.50 mm/yr to 5.00 mm/yr (2018–2019) in the study area. The deformation trends in the Qinghai–Tibet Railway (QTR) and Qinghai–Tibet Highway (QTH) regions are stable, ranging from −18.00 mm to 6 mm. The InSAR results of Sentinel-1 and TerraSAR-X data show that seasonal deformation trends are consistent, exhibiting good correlations 0.78 and 0.84, and the seasonal and linear deformation rates of different ground targets are clearly different on the Beiluhe basin. Additionally, there are different time lags between the maximum freezing uplift or thawing subsidence and the maximum or minimum temperature for the different ground target areas. The deformation values of the alpine meadow and floodplain areas are higher compared with the alpine desert and barren areas, and the time lags of the freezing and thawing periods based on the Sentinel-1 results are longest in the alpine desert area, that is, 86 days and 65 days, respectively. Our research has important reference significance for the seasonal dynamic monitoring of different types of seasonal deformation and the extensive investigations of permafrost in Qinghai Tibet Plateau.

In order to explore the applicability of the rejuvenated asphalt with wood tar as the main raw material, the orthogonal test was used to determine the optimal ratio of wood tar-based rejuvenator. The physical properties, rheological properties and components of matrix asphalt, aged asphalt, wood tar-based rejuvenated asphalt and commercial RA-102# rejuvenated asphalt were tested and compared. The results show that the optimal ratio of wood tar-based rejuvenator is 15wt% wood tar, 0.3wt% biomass fiber, 5wt% plasticizer, 0.3wt% compatibilizer, and 1wt% stabilizer of the mass of aged asphalt. Wood tar-based rejuvenator can restore the physical properties of the aged asphalt to meet the specification requirements. The synergistic effect of biomass fiber and plasticizer make the wood tar-based rejuvenated asphalt has good resistance to accumulated permanent deformation, but its low-temperature cracking resistance needs to be further improved. During the rejuvenation process of aged asphalt, the colloidal state changes from gel-state to sol-state, characterizing that the viscosity of asphalt decreased and the fluidity increased. Wood tar-based rejuvenator can react with aged asphalt to weaken the vibration strength of carbonyl and sulfoxide groups, so as to realize the recovery of service performance. Wood tar-based rejuvenator has better environmental protection and applicability, which is worthy of further study and promotion.

Permafrost is widely distributed in the Tibetan Plateau. Seasonal freeze−thaw cycles of permafrost result in upward and downward surface displacement. Multitemporal interferometric synthetic aperture radar (MT-InSAR) observations provide an effective method for monitoring permafrost displacement under difficult terrain and climatic conditions. In this study, a seasonal sinusoidal model-based new small baselines subset (NSBAS) chain was adopted to obtain a deformation time series. An experimental study was carried out using 33 scenes of Sentinel-1 data (S-1) from 28 November 2017 to 29 December 2018 with frequent revisit (12 days) observations. The spatial and temporal characteristics of the surface displacements variation combined with different types of surface land cover, elevation and surface temperature factors were analyzed. The results revealed that the seasonal changes observed in the time series of ground movements, induced by freeze−thaw cycles were observed on flat surfaces of sedimentary basins and mountainous areas with gentle slopes. The estimated seasonal oscillations ranged from 2 mm to 30 mm, which were smaller in Alpine deserts than in Alpine meadows. In particular, there were significant systematic differences in seasonal surface deformation between areas near mountains and sedimentary basins. It was also found that the time series of deformation was consistent with the variation of surface temperature. Based on soil moisture active/passive (SMAP) L4 surface and root zone soil moisture data, the deformation analysis influenced by soil moisture factors was also carried out. The comprehensive analysis of deformation results and auxiliary data (elevation, soil moisture and surface temperature et al.) provides important insights for the monitoring of the seasonal freeze-thaw cycles in the Tibetan Plateau.

Conventionally laminated spacer composites are extensively applied in many fields owing to their light weight. However, their impact resistance, interlaminar strength, and integrity are poor. In order to overcome these flaws, the zigzag-shaped 3D woven spacer composites were rationally designed. The zigzag-shaped 3D woven spacer fabrics with the basalt fiber filaments tows 400 tex (metric count of yarn) used as warp and weft yarns were fabricated on a common loom with low-cost processing. The zigzag-shaped 3D woven spacer composites were obtained using the VARTM (vacuum-assisted resin transfer molding) process. The three-point bending deformation and effects of damage in zigzag-shaped 3D woven spacer composites were studied both in experiment and using the finite element method (FEM). The bending properties of zigzag-shaped 3D woven spacer composites with different direction, different numbers of weaving cycle, and different heights were tested in experiments. In FEM simulation, the geometrical model was established to analyze the deformation and damage based on the 3D woven composite structure. Compared with data obtained from the experiments and FEM simulation, the results show good agreement and also prove the validity of the model. Based on the FEM results, the deformation, damage, and propagation of stress obtained from the model are very helpful in analyzing the failure mechanism of zigzag-shaped 3D woven composites. Furthermore, the results can significantly guide the fabrication process of real composite materials.

Parkinson’s disease (PD) is the second most common neurodegenerative disease affecting people over age 55. Oxidative stress actively participates in the dopaminergic (DA) neuron degeneration of PD. Xyloketals are a series of natural compounds from marine mangrove fungus strain No. 2508 that have been reported to protect against neurotoxicity through their antioxidant properties. However, their protection versus 1-methyl-4-phenylpyridinium (MPP+)-induced neurotoxicity is only modest, and appropriate structural modifications are necessary to discover better candidates for treating PD. In this work, we designed and synthesized 39 novel xyloketal derivatives (1–39) in addition to the previously reported compound, xyloketal B. The neuroprotective activities of all 40 compounds were evaluated in vivo via respiratory burst assays and longevity-extending assays. During the zebrafish respiratory burst assay, compounds 1, 9, 23, 24, 36 and 39 strongly attenuated reactive oxygen species (ROS) generation at 50 μM. In the Caenorhabditis elegans longevity-extending assay, compounds 1, 8, 15, 16 and 36 significantly extended the survival rates (p < 0.005 vs. dimethyl sulfoxide (DMSO)). A total of 15 compounds were tested for the treatment of Parkinson’s disease using the MPP+-induced C. elegans model, and compounds 1 and 8 exhibited the highest activities (p < 0.005 vs. MPP+). In the MPP+-induced C57BL/6 mouse PD model, 40 mg/kg of 1 and 8 protected against MPP+-induced dopaminergic neurodegeneration and increased the number of DA neurons from 53% for the MPP+ group to 78% and 74%, respectively (p < 0.001 vs. MPP+ group). Thus, these derivatives are novel candidates for the treatment of PD.

Soil moisture products acquired from passive satellite missions have been widely applied in environmental processes. A primary challenge for the use of soil moisture products from passive sensors is their reliability. It is crucial to evaluate the reliability of those products before they can be routinely used at a global scale. In this paper, we evaluated the Soil Moisture Active/Passive (SMAP) and the Advanced Microwave Scanning Radiometer (AMSR2) radiometer soil moisture products against in situ measurements collected from American networks with four statistics, including the mean difference (MD), the root mean squared difference (RMSD), the unbiased root mean square error (ubRMSE) and the correlation coefficient (R). The evaluation results of SMAP and AMSR2 soil moisture products were compared. Moreover, the triple collocation (TC) error model was used to assess the error among AMSR2, SMAP and in situ data. The monthly average and daily AMSR2 and SMAP soil moisture data were analyzed. Different spatial series, temporal series and combined spatial-temporal analysis were carried out. The results reveal that SMAP soil moisture retrievals are generally better than AMSR2 soil moisture data. The remotely sensed retrievals show the best agreement with in situ measurements over the central Great Plains and cultivated crops throughout the year. In particular, SMAP soil moisture data shows a stable pattern for capturing the spatial distribution of surface soil moisture. Further studies are required for better understanding the SMAP soil moisture product.